Responses API

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When to use it

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Quick start

curl https://api.venice.ai/api/v1/responses \
  -H "Authorization: Bearer $VENICE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "venice-uncensored",
    "input": "Explain why the sky is blue in one sentence.",
    "venice_parameters": { "include_venice_system_prompt": false }
  }'

from openai import OpenAI

client = OpenAI(base_url="https://api.venice.ai/api/v1", api_key="YOUR_VENICE_API_KEY")

response = client.responses.create(
    model="venice-uncensored",
    input="Explain why the sky is blue in one sentence.",
    extra_body={"venice_parameters": {"include_venice_system_prompt": False}},
)
print(response.output_text)

import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.venice.ai/api/v1", apiKey: process.env.VENICE_API_KEY });

const response = await client.responses.create({
  model: "venice-uncensored",
  input: "Explain why the sky is blue in one sentence.",
  venice_parameters: { include_venice_system_prompt: false },
});
console.log(response.output_text);

{
  "id": "resp_...",
  "object": "response",
  "model": "venice-uncensored-1-2",
  "status": "completed",
  "output": [
    {
      "type": "message",
      "id": "msg_...",
      "role": "assistant",
      "status": "completed",
      "content": [{ "type": "output_text", "text": "Sunlight scatters off air molecules...", "annotations": [] }]
    }
  ],
  "usage": { "input_tokens": 18, "output_tokens": 21, "total_tokens": 39 }
}

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How requests are served

• Native. Requests for OpenAI models are forwarded to OpenAI’s Responses API without translation. This covers every openai-* model except openai-gpt-oss-120b. Response items, IDs, reasoning, and stream events come back exactly as OpenAI returns them.
• Translated. Every other model, plus openai-gpt-oss-120b, goes through a translation layer: Venice converts the request into a Chat Completions request, runs it, and converts the result back. Anything the Chat Completions format cannot express is ignored or rejected. See Limitations.

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Conversations are stateless

history = [{"role": "user", "content": "What is the weather in Paris? Use the tool."}]
tools = [{
    "type": "function",
    "name": "get_weather",
    "description": "Get the current weather for a city",
    "parameters": {"type": "object", "properties": {"city": {"type": "string"}}, "required": ["city"]},
}]

first = client.responses.create(model="venice-uncensored", input=history, tools=tools)
call = next(item for item in first.output if item.type == "function_call")

history += first.output
history.append({"type": "function_call_output", "call_id": call.call_id, "output": '{"temp_c": 18}'})

second = client.responses.create(model="venice-uncensored", input=history, tools=tools)
print(second.output_text)

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Native mode

• instructions, applied as written.
• Structured outputs with text.format. OpenAI validates schemas strictly, so an invalid schema returns 400. For example, strict: true requires additionalProperties: false, and json_object requires the word “json” somewhere in the input.
• Function tools and tool_choice in OpenAI’s Responses shape {"type": "function", "name": "..."}, plus parallel tool calls.
• Client-executed tools: custom (freeform input), namespace, tool_search, apply_patch, shell and local_shell with a local environment, and computer use.
• Reasoning summaries, on by default. Reasoning models always return encrypted_content on reasoning items. Send those items back in input on the next turn to keep the model’s reasoning context.
• Prompt caching with prompt_cache_key. Venice scopes the key to your account, so it never shares a cache with other users, and returns your original key in the response.
• Image inputs, including detail: "original", and input_file with inline file_data.
• Pro models (*-pro), which run OpenAI’s Pro reasoning mode automatically.

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Streaming

• Reasoning text streams as response.reasoning.delta, not as OpenAI’s reasoning summary events.
• When web search runs, a response.web_search.done event carries the search results before the answer streams.

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Translated mode parameters

• instructions are applied as a system message.
• Custom tools return custom_tool_call items with the raw input. If a model returns malformed custom-tool arguments, or calls a tool that is not declared in the request, the call comes back as an ordinary function_call with the original arguments, so your client can report a tool error and continue.
• While a custom tool’s input streams, its call item and later items can arrive only after the input is complete. The stream sends SSE keep-alive comments while it waits.
• Image detail: "original" is sent as high to providers that do not support it.

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Limitations

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Related

• API reference for POST /responses
• Function calling
• Reasoning models
• OpenAI migration guide